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I need a clear, evidence-based report that compares the performance of today’s most widely cited object-detection algorithms. The focus is strictly on Computer Vision, zeroing in on Object Detection, and the core goal is to evaluate how the main approaches stack up against each other in terms of accuracy, speed, computational cost, and real-world suitability. Scope • Analyse at least three state-of-the-art methods—think Faster R-CNN, SSD, YOLO (v7/8), DETR or similar. • Draw all claims from peer-reviewed journals, top-tier conference papers, or authoritative benchmark leaderboards (e.g., COCO, PASCAL VOC). • Present metrics consistently (mAP, FPS, FLOPs, params, latency) so direct comparison is effortless. • Highlight strengths, weaknesses, and trad...

I need a clear, evidence-based report that compares the performance of today’s most widely cited object-detection algorithms. The focus is strictly on Computer Vision, zeroing in on Object Detection, and the core goal is to evaluate how the main approaches stack up against each other in terms of accuracy, speed, computational cost, and real-world suitability. Scope • Analyse at least three state-of-the-art methods—think Faster R-CNN, SSD, YOLO (v7/8), DETR or similar. • Draw all claims from peer-reviewed journals, top-tier conference papers, or authoritative benchmark leaderboards (e.g., COCO, PASCAL VOC). • Present metrics consistently (mAP, FPS, FLOPs, params, latency) so direct comparison is effortless. • Highlight strengths, weaknesses, and trad...